Computational simulations of anatomical structures and body surface electrode positioning

1. A system, comprising:

at least one processor; and

at least one memory including program code which when executed by the at least one processor provides operations comprising: receiving two dimensional images of an internal anatomy of a subject;

accessing a library that maps each of a plurality of computed two-dimensional representations of a simulated three-dimensional representation to an internal anatomy that is not derived from a first subject;

for each of a plurality of computed two-dimensional representations, generating a similarity index indicating closeness of a match between the first two-dimensional image depicting the first internal anatomy of the first subject and that computed two-dimensional representation;

identifying a computed two-dimensional representation based on closeness of the match as indicated by the similarity index for that computed two-dimensional representation; and

generating an output including the simulated three-dimensional representation that corresponds to the identified computed two-dimensional representation as a representation of the first internal anatomy of the first subject.

2. The system of claim 1 , wherein the operations further comprise:

generating the library including by generating, based on a first three-dimensional representation of a second internal anatomy of a second subject, the first simulated three-dimensional representation, the first simulated three-dimensional representation being generated by at least varying one or more attributes of the second internal anatomy of the second subject.

3. The system of claim 2 , wherein the one or more attributes include a skeletal property, an organ geometry, a musculature, and/or a subcutaneous fat distribution.

4. The system of claim 2 , wherein the library is further generated to include the first three-dimensional representation of the second internal anatomy of the second subject and/or a second three-dimensional representation of a third internal anatomy of a third subject having at least one attribute that is different from that attribute of the second internal anatomy of the second subject.

5. The system of claim 2 , wherein the generating of the library further includes generating, based at least on the first simulated three-dimensional representation, the first computed two-dimensional image.

6. The system of claim 5 , wherein the generating of the first computed two-dimensional image includes determining, based at least on a density and/or a transmissivity of one or more tissues included in the first simulated three-dimensional representation, a quantity of radiation able to pass through the one or more tissues included in the first simulated three-dimensional representation to form the first computed two-dimensional image.

7. The system of claim 2 , wherein the first three-dimensional representation of the second internal anatomy of the second subject comprises a computed tomography (CT) scan and/or a magnetic resonance imaging (MRI) scan depicting the second internal anatomy of the second subject.

8. The system of claim 1 , wherein the first simulated three-dimensional representation is further associated with a diagnosis of a condition depicted in the first simulated three-dimensional representation, and wherein the output is further generated to include the diagnosis.

9. The system of claim 1 , wherein the operations further comprise:

determining a first similarity index indicating a closeness of the match between the first computed two-dimensional image and the two-dimensional image depicting the first internal anatomy of the first subject, the first simulated three-dimensional representation identified as corresponding to the first internal anatomy of the first subject based at least on the first similarity index exceeding a threshold value and/or the first similarity index being greater than a second similarity index indicating a closeness of a match between a second computed two-dimensional image corresponding to a second simulated three-dimensional representation and the two-dimensional image depicting the first internal anatomy of the first subject.

10. The system of claim 1 , wherein the first computed two-dimensional image is determined to match the two-dimensional image depicting the first internal anatomy of the first subject by at least applying an image comparison technique.

11. The system of claim 10 , wherein the image comparison technique comprises scale invariant feature transform (SIFT), speed up robust feature (SURF), binary robust independent elementary features (BRIEF), and/or oriented FAST and rotated BRIEF (ORB).

12. The system of claim 10 , wherein the image comparison technique comprises a machine learning model.

13. The system of claim 12 , wherein the machine learning model comprises an autoencoder and/or a neural network.

14. The system of claim 1 , wherein the operations further comprise:

determining, based at least on the two-dimensional image depicting the first internal anatomy of the first subject, a lead placement for a recording device configured to measure an electrical activity of an organ, the recording device including one or more leads configured to detect a change in voltage on a body surface corresponding to the electrical activity of the organ; and

generating, based at least on the lead placement and the first simulated three-dimensional representation of the first internal anatomy of the first subject, a simulation of the electrical activity measured by the recording device.

15. The system of claim 14 , wherein the simulation of the electrical activity measured by the recording device includes a signal detected by each of the one or more leads included in the recording device.

16. The system of claim 14 , wherein the recording device is configured to perform an electrocardiography (ECG) and/or an electroencephalography (EEG).

17. The system of claim 14 , wherein the output is further generated to include the lead placement and/or the simulation of the electrical activity measured by the recording device.

18. The system of claim 1 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a mismatch between a demographics and/or a vital statistics of the first subject and a second subject depicted in the second simulated three-dimensional representation.

19. The system of claim 1 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a condition depicted in the second simulated three-dimensional representation being inconsistent with one or more symptoms of the first subject.

20. The system of claim 1 , wherein the operations further comprise:

providing, to a client, the output including by sending, to the client, at least a portion of the output and/or generating a user interface configured to display at least the portion of the output at the client.

21. A computer-implemented method, comprising: receiving two dimensional images of an internal anatomy of a subject;

accessing a library including a plurality of computed two-dimensional representations corresponding to simulated three-dimensional representations of internal anatomies that are not derived from a first subject;

for each of a plurality of computed two-dimensional representations, generating a similarity index indicating closeness of a match between the first two-dimensional image depicting the first internal anatomy of the first subject and that computed two-dimensional representation;

identifying a computed two-dimensional representation based on closeness of the match as indicated by the similarity index for that computed two-dimensional representation; and

generating an output including the simulated three-dimensional representation that corresponds to the identified computed two-dimensional representation as a representation of the first internal anatomy of the first subject.

22. The method of claim 21 , further comprising:

generating the library including by generating, based on a first three-dimensional representation of a second internal anatomy of a second subject, the first simulated three-dimensional representation, the first simulated three-dimensional representation being generated by at least varying one or more attributes of the second internal anatomy of the second subject.

23. The method of claim 22 , wherein the one or more attributes include a skeletal property, an organ geometry, a musculature, and/or a subcutaneous fat distribution.

24. The method of claim 22 , wherein the library is further generated to include the first three-dimensional representation of the second internal anatomy of the second subject and/or a second three-dimensional representation of a third internal anatomy of a third subject having at least one different attribute than the second internal anatomy of the second subject.

25. The method of claim 22 , wherein the generating of the library further includes generating, based at least on the first simulated three-dimensional representation, the first computed two-dimensional image.

26. The method of claim 25 , wherein the generating of the first computed two-dimensional image includes determining, based at least on a density and/or a transmissivity of one or more tissues included in the first simulated three-dimensional representation, a quantity of radiation able to pass through the one or more tissues included in the first simulated three-dimensional representation to form the first computed two-dimensional image.

27. The method of claim 22 , wherein the first three-dimensional representation of the second internal anatomy of the second subject comprises a computed tomography (CT) scan and/or a magnetic resonance imaging (MRI) scan depicting the second internal anatomy of the second subject.

28. The method of claim 21 , wherein the first simulated three-dimensional representation is further associated with a diagnosis of a condition depicted in the first simulated three-dimensional representation, and wherein the output is further generated to include the diagnosis.

29. The method of claim 21 , further comprising:

determining a first similarity index indicating a closeness of the match between the first computed two-dimensional image and the two-dimensional image depicting the first internal anatomy of the first subject, the first simulated three-dimensional representation identified as corresponding to the first internal anatomy of the first subject based at least on the first similarity index exceeding a threshold value and/or the first similarity index being greater than a second similarity index indicating a closeness of a match between a second computed two-dimensional image corresponding to a second simulated three-dimensional representation and the two-dimensional image depicting the first internal anatomy of the first subject.

30. The method of claim 21 , wherein the first computed two-dimensional image is determined to match the two-dimensional image depicting the first internal anatomy of the first subject by at least applying an image comparison technique.

31. The method of claim 30 , wherein the image comparison technique comprises scale invariant feature transform (SIFT), speed up robust feature (SURF), binary robust independent elementary features (BRIEF), and/or oriented FAST and rotated BRIEF (ORB).

32. The method of claim 30 , wherein the image comparison technique comprises a machine learning model.

33. The method of claim 32 , wherein the machine learning model comprises an autoencoder and/or a neural network.

34. The method of claim 21 , further comprising:

determining, based at least on the two-dimensional image depicting the first internal anatomy of the first subject, a lead placement for a recording device configured to measure an electrical activity of an organ, the recording device including one or more leads configured to detect a change in voltage on a body surface corresponding to the electrical activity of the organ; and

generating, based at least on the lead placement and the first simulated three-dimensional representation of the first internal anatomy of the first subject, a simulation of the electrical activity measured by the recording device.

35. The method of claim 34 , wherein the simulation of the electrical activity measured by the recording device includes a signal detected by each of the one or more leads included in the recording device.

36. The method of claim 34 , wherein the recording device is configured to perform an electrocardiography (ECG) and/or an electroencephalography (EEG).

37. The method of claim 34 , wherein the output is further generated to include the lead placement and/or the simulation of the electrical activity measured by the recording device.

38. The method of claim 21 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a mismatch between a demographics and/or a vital statistics of the first subject and a second subject depicted in the second simulated three-dimensional representation.

39. The method of claim 21 , wherein the identifying of the first simulated three-dimensional representation further includes eliminating a second simulated three-dimensional representation based at least on a condition depicted in the second simulated three-dimensional representation being inconsistent with one or more symptoms of the first subject.

40. The method of claim 21 , further comprising:

providing, to a client, the output including by sending, to the client, at least a portion of the output and/or generating a user interface configured to display at least the portion of the output at the client.

41. A non-transitory computer readable medium storing instructions, which when executed by at least one data processor, result in operations comprising: receiving two dimensional images of an internal anatomy of a subject;

accessing a library including a plurality of computed two-dimensional representations corresponding to simulated three-dimensional representations of internal anatomies that are not derived from a first subject;

for each of a plurality of computed two-dimensional representations, generating a similarity index indicating closeness of a match between the first two-dimensional image depicting the first internal anatomy of the first subject and that computed two-dimensional representation;

identifying a computed two-dimensional representation based on closeness of the match as indicated by the similarity index for that computed two-dimensional representation; and

generating an output including the simulated three-dimensional representation that corresponds to the identified computed two-dimensional representation as a representation of the first internal anatomy of the first subject.

42. An apparatus, comprising: receiving two dimensional images of an internal anatomy of a subject;

a library including a plurality of computed two-dimensional representations corresponding to simulated three-dimensional representations of internal anatomies that are not derived from a first subject; and

means for, for each of a plurality of computed two-dimensional representations, generating a similarity index indicating closeness of a match between the first two-dimensional image depicting the first internal anatomy of the first subject and that computed two-dimensional representation;

means for identifying a computed two-dimensional representation based on closeness of the match as indicated by the similarity index for that computed two-dimensional representation; and

means for generating an output including the simulated three-dimensional representation that corresponds to the identified computed two-dimensional representation as a representation of the first internal anatomy of the first subject.

43. A computer-implemented method, comprising: receiving two dimensional images of an internal anatomy of a subject;

identifying, in a library including a plurality of computed two-dimensional representations corresponding to simulated three-dimensional representations of internal anatomies that are not derived from a first subject, a first simulated three-dimensional representation corresponding to a first internal anatomy of the first subject, the first simulated three-dimensional representation being identified based at least on a match between the first computed two-dimensional image corresponding to the first simulated three-dimensional representation and a two-dimensional image depicting the first internal anatomy of the first subject; and

generating an output including the simulated three-dimensional representation of the first internal anatomy of the first subject

wherein the first computed two-dimensional image is generated based on a quantity of radiation able to pass through one or more tissues included in the first simulated three-dimensional representation to form the first computed two-dimensional image based at least on a density and/or a transmissivity of the one or more tissues included in the first simulated three-dimensional representation.